Project Summary Chronic lymphocytic leukemia (CLL) is a common adult leukemia marked by clonal expansions of mature B cells in peripheral blood, bone marrow and lymph nodes. In recent years, improvements in the development of targeted therapies and combination chemotherapeutic regimens have increased patient survival, but resistance to treatment remains a major clinical and scientific challenge. Prior studies in the Wu lab have demonstrated readily detectable shifts in the clonal composition of CLL cells occurring with therapy response and with the onset of resistance, that are associated with diverse genetic and epigenetic alterations. These studies have provided important but limited information, and lead us to hypothesize that integration of genetic, epigenetic and gene expression data of key resistance-mediating cell subpopulations will provide deeper understanding of the mechanisms underlying changes in clonal dynamics. Barcode sequencing is one method for quantifying the relative lineage frequencies in a tumor population with high resolution. However, until now DNA barcoding has been limited to quantification of lineages, without detailed molecular and functional analysis of those lineages. In previous work supported by the Innovative Molecular Analysis Technologies (iMAT) program at NCI, the Brock lab developed a novel barcoding technology based on guide RNA barcodes. These expressed barcodes complex with the transcriptional activator variant of Cas9 and actuate gene expression. Activation of lineage-specific reporter gene expression allows for high-resolution lineage tracking and subsequent isolation of purified cell lineages for downstream analysis. The ability to concurrently track clonal fitness dynamics and generate clone- specific genomic and transcriptomic data over longitudinal studies provides a new tool for dissecting the response of a tumor population to therapeutics. In this project, we will utilize this new expressed barcode technology platform to directly address our hypothesis, namely to identify, isolate, purify and characterize (by whole-exome sequencing, ATAC-seq, BH3 profiling) CLL subpopulations that display resistance to first-line chemotherapy with combination fludarabine/mafosfamide and to second-line targeted drug treatment with the BCL2-inhibitor venetoclax. We propose to utilize COLBERT in in vitro studies to characterize the treatment and resistance response of the model cell line HG3 (Aim 1); and to adapt COLBERT for studying the evolutionary response of murine CLL-like cells to treatment in an in vivo immune-competent system (Aim 2), using the MDR mouse line, such that we can additionally evaluate the impact of leukemia cell evolution and drug response on the local leukemia microenvironment. Altogether, we anticipate that the proposed collaborative work will pioneer the ability to unlock the molecular and phenotypic basis of therapeutic resistance at single cell resolution, and will provide key insights that have direct relevance to the clinical management of our patients with CLL.